Overview

Dataset statistics

Number of variables51
Number of observations2261067
Missing cells0
Missing cells (%)0.0%
Duplicate rows216
Duplicate rows (%)< 0.1%
Total size in memory879.8 MiB
Average record size in memory408.0 B

Variable types

Categorical49
Numeric2

Warnings

Dataset has 216 (< 0.1%) duplicate rowsDuplicates
DT_NOTIFIC has a high cardinality: 645 distinct values High cardinality
positivo_para3 is highly correlated with positivo_para4High correlation
positivo_para4 is highly correlated with positivo_para3High correlation
tempo_alta_obito_final has 22683 (1.0%) zeros Zeros

Reproduction

Analysis started2021-10-11 02:36:49.006763
Analysis finished2021-10-11 02:42:29.270461
Duration5 minutes and 40.26 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

DT_NOTIFIC
Categorical

HIGH CARDINALITY

Distinct645
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
2021-03-15
 
11662
2021-03-22
 
11489
2021-03-29
 
11280
2021-05-04
 
10740
2021-03-30
 
10375
Other values (640)
2205521 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters22610670
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2020-10-01
2nd row2020-07-01
3rd row2020-01-27
4th row2020-02-13
5th row2020-02-26

Common Values

ValueCountFrequency (%)
2021-03-1511662
 
0.5%
2021-03-2211489
 
0.5%
2021-03-2911280
 
0.5%
2021-05-0410740
 
0.5%
2021-03-3010375
 
0.5%
2021-03-2410313
 
0.5%
2021-03-1610016
 
0.4%
2021-08-039823
 
0.4%
2021-03-259769
 
0.4%
2021-03-189549
 
0.4%
Other values (635)2156051
95.4%

Length

2021-10-10T23:42:29.490149image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-03-1511662
 
0.5%
2021-03-2211489
 
0.5%
2021-03-2911280
 
0.5%
2021-05-0410740
 
0.5%
2021-03-3010375
 
0.5%
2021-03-2410313
 
0.5%
2021-03-1610016
 
0.4%
2021-08-039823
 
0.4%
2021-03-259769
 
0.4%
2021-03-189549
 
0.4%
Other values (635)2156051
95.4%

Most occurring characters

ValueCountFrequency (%)
06191526
27.4%
25727397
25.3%
-4522134
20.0%
12761068
12.2%
3610947
 
2.7%
5544432
 
2.4%
6526096
 
2.3%
4499162
 
2.2%
7471463
 
2.1%
8413370
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number18088536
80.0%
Dash Punctuation4522134
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
06191526
34.2%
25727397
31.7%
12761068
15.3%
3610947
 
3.4%
5544432
 
3.0%
6526096
 
2.9%
4499162
 
2.8%
7471463
 
2.6%
8413370
 
2.3%
9343075
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
-4522134
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common22610670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
06191526
27.4%
25727397
25.3%
-4522134
20.0%
12761068
12.2%
3610947
 
2.7%
5544432
 
2.4%
6526096
 
2.3%
4499162
 
2.2%
7471463
 
2.1%
8413370
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII22610670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
06191526
27.4%
25727397
25.3%
-4522134
20.0%
12761068
12.2%
3610947
 
2.7%
5544432
 
2.4%
6526096
 
2.3%
4499162
 
2.2%
7471463
 
2.1%
8413370
 
1.8%

tempo_alta_obito_final
Real number (ℝ)

ZEROS

Distinct660
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean83.45533989
Minimum-999
Maximum703
Zeros22683
Zeros (%)1.0%
Negative7208
Negative (%)0.3%
Memory size17.3 MiB
2021-10-10T23:42:29.592877image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-999
5-th percentile4
Q117
median55
Q3137
95-th percentile253
Maximum703
Range1702
Interquartile range (IQR)120

Descriptive statistics

Standard deviation103.8061926
Coefficient of variation (CV)1.243853212
Kurtosis36.43511312
Mean83.45533989
Median Absolute Deviation (MAD)46
Skewness-2.956847523
Sum188698115
Variance10775.72561
MonotonicityNot monotonic
2021-10-10T23:42:29.708568image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
737504
 
1.7%
1037491
 
1.7%
837012
 
1.6%
936958
 
1.6%
1536735
 
1.6%
1336559
 
1.6%
1436337
 
1.6%
1136037
 
1.6%
635249
 
1.6%
1234674
 
1.5%
Other values (650)1896511
83.9%
ValueCountFrequency (%)
-9997208
 
0.3%
022683
1.0%
120761
0.9%
219184
0.8%
326051
1.2%
431012
1.4%
534373
1.5%
635249
1.6%
737504
1.7%
837012
1.6%
ValueCountFrequency (%)
7031
 
< 0.1%
7021
 
< 0.1%
7011
 
< 0.1%
6994
< 0.1%
6981
 
< 0.1%
6964
< 0.1%
6931
 
< 0.1%
6925
< 0.1%
6912
 
< 0.1%
6906
< 0.1%

febre
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Sim
1238255 
Nao
658131 
Nulo
333558 
Ignorado
 
31123

Length

Max length8
Median length3
Mean length3.216346088
Min length3

Characters and Unicode

Total characters7272374
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim1238255
54.8%
Nao658131
29.1%
Nulo333558
 
14.8%
Ignorado31123
 
1.4%

Length

2021-10-10T23:42:29.907378image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:29.954257image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
sim1238255
54.8%
nao658131
29.1%
nulo333558
 
14.8%
ignorado31123
 
1.4%

Most occurring characters

ValueCountFrequency (%)
S1238255
17.0%
i1238255
17.0%
m1238255
17.0%
o1053935
14.5%
N991689
13.6%
a689254
9.5%
u333558
 
4.6%
l333558
 
4.6%
I31123
 
0.4%
g31123
 
0.4%
Other values (3)93369
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5011307
68.9%
Uppercase Letter2261067
31.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1238255
24.7%
m1238255
24.7%
o1053935
21.0%
a689254
13.8%
u333558
 
6.7%
l333558
 
6.7%
g31123
 
0.6%
n31123
 
0.6%
r31123
 
0.6%
d31123
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S1238255
54.8%
N991689
43.9%
I31123
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin7272374
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1238255
17.0%
i1238255
17.0%
m1238255
17.0%
o1053935
14.5%
N991689
13.6%
a689254
9.5%
u333558
 
4.6%
l333558
 
4.6%
I31123
 
0.4%
g31123
 
0.4%
Other values (3)93369
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7272374
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1238255
17.0%
i1238255
17.0%
m1238255
17.0%
o1053935
14.5%
N991689
13.6%
a689254
9.5%
u333558
 
4.6%
l333558
 
4.6%
I31123
 
0.4%
g31123
 
0.4%
Other values (3)93369
 
1.3%

tosse
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Sim
1516540 
Nao
451250 
Nulo
267372 
Ignorado
 
25905

Length

Max length8
Median length3
Mean length3.175535267
Min length3

Characters and Unicode

Total characters7180098
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim1516540
67.1%
Nao451250
 
20.0%
Nulo267372
 
11.8%
Ignorado25905
 
1.1%

Length

2021-10-10T23:42:30.312438image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:30.367325image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
sim1516540
67.1%
nao451250
 
20.0%
nulo267372
 
11.8%
ignorado25905
 
1.1%

Most occurring characters

ValueCountFrequency (%)
S1516540
21.1%
i1516540
21.1%
m1516540
21.1%
o770432
10.7%
N718622
10.0%
a477155
 
6.6%
u267372
 
3.7%
l267372
 
3.7%
I25905
 
0.4%
g25905
 
0.4%
Other values (3)77715
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4919031
68.5%
Uppercase Letter2261067
31.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1516540
30.8%
m1516540
30.8%
o770432
15.7%
a477155
 
9.7%
u267372
 
5.4%
l267372
 
5.4%
g25905
 
0.5%
n25905
 
0.5%
r25905
 
0.5%
d25905
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S1516540
67.1%
N718622
31.8%
I25905
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin7180098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1516540
21.1%
i1516540
21.1%
m1516540
21.1%
o770432
10.7%
N718622
10.0%
a477155
 
6.6%
u267372
 
3.7%
l267372
 
3.7%
I25905
 
0.4%
g25905
 
0.4%
Other values (3)77715
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII7180098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1516540
21.1%
i1516540
21.1%
m1516540
21.1%
o770432
10.7%
N718622
10.0%
a477155
 
6.6%
u267372
 
3.7%
l267372
 
3.7%
I25905
 
0.4%
g25905
 
0.4%
Other values (3)77715
 
1.1%

dispneia
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Sim
1574868 
Nao
413810 
Nulo
249960 
Ignorado
 
22429

Length

Max length8
Median length3
Mean length3.160147842
Min length3

Characters and Unicode

Total characters7145306
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowIgnorado
3rd rowSim
4th rowSim
5th rowNao

Common Values

ValueCountFrequency (%)
Sim1574868
69.7%
Nao413810
 
18.3%
Nulo249960
 
11.1%
Ignorado22429
 
1.0%

Length

2021-10-10T23:42:30.528553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:30.583406image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
sim1574868
69.7%
nao413810
 
18.3%
nulo249960
 
11.1%
ignorado22429
 
1.0%

Most occurring characters

ValueCountFrequency (%)
S1574868
22.0%
i1574868
22.0%
m1574868
22.0%
o708628
9.9%
N663770
9.3%
a436239
 
6.1%
u249960
 
3.5%
l249960
 
3.5%
I22429
 
0.3%
g22429
 
0.3%
Other values (3)67287
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4884239
68.4%
Uppercase Letter2261067
31.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1574868
32.2%
m1574868
32.2%
o708628
14.5%
a436239
 
8.9%
u249960
 
5.1%
l249960
 
5.1%
g22429
 
0.5%
n22429
 
0.5%
r22429
 
0.5%
d22429
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S1574868
69.7%
N663770
29.4%
I22429
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7145306
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1574868
22.0%
i1574868
22.0%
m1574868
22.0%
o708628
9.9%
N663770
9.3%
a436239
 
6.1%
u249960
 
3.5%
l249960
 
3.5%
I22429
 
0.3%
g22429
 
0.3%
Other values (3)67287
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7145306
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1574868
22.0%
i1574868
22.0%
m1574868
22.0%
o708628
9.9%
N663770
9.3%
a436239
 
6.1%
u249960
 
3.5%
l249960
 
3.5%
I22429
 
0.3%
g22429
 
0.3%
Other values (3)67287
 
0.9%

diarreia
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1305910 
Nulo
623487 
Sim
283007 
Ignorado
 
48663

Length

Max length8
Median length3
Mean length3.383359715
Min length3

Characters and Unicode

Total characters7650003
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowNao
3rd rowSim
4th rowNao
5th rowNao

Common Values

ValueCountFrequency (%)
Nao1305910
57.8%
Nulo623487
27.6%
Sim283007
 
12.5%
Ignorado48663
 
2.2%

Length

2021-10-10T23:42:30.741401image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:30.796725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1305910
57.8%
nulo623487
27.6%
sim283007
 
12.5%
ignorado48663
 
2.2%

Most occurring characters

ValueCountFrequency (%)
o2026723
26.5%
N1929397
25.2%
a1354573
17.7%
u623487
 
8.2%
l623487
 
8.2%
S283007
 
3.7%
i283007
 
3.7%
m283007
 
3.7%
I48663
 
0.6%
g48663
 
0.6%
Other values (3)145989
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5388936
70.4%
Uppercase Letter2261067
29.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2026723
37.6%
a1354573
25.1%
u623487
 
11.6%
l623487
 
11.6%
i283007
 
5.3%
m283007
 
5.3%
g48663
 
0.9%
n48663
 
0.9%
r48663
 
0.9%
d48663
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N1929397
85.3%
S283007
 
12.5%
I48663
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Latin7650003
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2026723
26.5%
N1929397
25.2%
a1354573
17.7%
u623487
 
8.2%
l623487
 
8.2%
S283007
 
3.7%
i283007
 
3.7%
m283007
 
3.7%
I48663
 
0.6%
g48663
 
0.6%
Other values (3)145989
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII7650003
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2026723
26.5%
N1929397
25.2%
a1354573
17.7%
u623487
 
8.2%
l623487
 
8.2%
S283007
 
3.7%
i283007
 
3.7%
m283007
 
3.7%
I48663
 
0.6%
g48663
 
0.6%
Other values (3)145989
 
1.9%

vomito
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1366544 
Nulo
647780 
Sim
196236 
Ignorado
 
50507

Length

Max length8
Median length3
Mean length3.398181478
Min length3

Characters and Unicode

Total characters7683516
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowNao
3rd rowSim
4th rowNao
5th rowNao

Common Values

ValueCountFrequency (%)
Nao1366544
60.4%
Nulo647780
28.6%
Sim196236
 
8.7%
Ignorado50507
 
2.2%

Length

2021-10-10T23:42:30.954687image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:31.011694image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1366544
60.4%
nulo647780
28.6%
sim196236
 
8.7%
ignorado50507
 
2.2%

Most occurring characters

ValueCountFrequency (%)
o2115338
27.5%
N2014324
26.2%
a1417051
18.4%
u647780
 
8.4%
l647780
 
8.4%
S196236
 
2.6%
i196236
 
2.6%
m196236
 
2.6%
I50507
 
0.7%
g50507
 
0.7%
Other values (3)151521
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5422449
70.6%
Uppercase Letter2261067
29.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2115338
39.0%
a1417051
26.1%
u647780
 
11.9%
l647780
 
11.9%
i196236
 
3.6%
m196236
 
3.6%
g50507
 
0.9%
n50507
 
0.9%
r50507
 
0.9%
d50507
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
N2014324
89.1%
S196236
 
8.7%
I50507
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Latin7683516
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2115338
27.5%
N2014324
26.2%
a1417051
18.4%
u647780
 
8.4%
l647780
 
8.4%
S196236
 
2.6%
i196236
 
2.6%
m196236
 
2.6%
I50507
 
0.7%
g50507
 
0.7%
Other values (3)151521
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7683516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2115338
27.5%
N2014324
26.2%
a1417051
18.4%
u647780
 
8.4%
l647780
 
8.4%
S196236
 
2.6%
i196236
 
2.6%
m196236
 
2.6%
I50507
 
0.7%
g50507
 
0.7%
Other values (3)151521
 
2.0%

garganta
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1234360 
Nulo
602323 
Sim
372400 
Ignorado
 
51984

Length

Max length8
Median length3
Mean length3.38134341
Min length3

Characters and Unicode

Total characters7645444
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowNao
3rd rowNao
4th rowNao
5th rowNao

Common Values

ValueCountFrequency (%)
Nao1234360
54.6%
Nulo602323
26.6%
Sim372400
 
16.5%
Ignorado51984
 
2.3%

Length

2021-10-10T23:42:31.165353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:31.221191image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1234360
54.6%
nulo602323
26.6%
sim372400
 
16.5%
ignorado51984
 
2.3%

Most occurring characters

ValueCountFrequency (%)
o1940651
25.4%
N1836683
24.0%
a1286344
16.8%
u602323
 
7.9%
l602323
 
7.9%
S372400
 
4.9%
i372400
 
4.9%
m372400
 
4.9%
I51984
 
0.7%
g51984
 
0.7%
Other values (3)155952
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5384377
70.4%
Uppercase Letter2261067
29.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1940651
36.0%
a1286344
23.9%
u602323
 
11.2%
l602323
 
11.2%
i372400
 
6.9%
m372400
 
6.9%
g51984
 
1.0%
n51984
 
1.0%
r51984
 
1.0%
d51984
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N1836683
81.2%
S372400
 
16.5%
I51984
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
Latin7645444
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1940651
25.4%
N1836683
24.0%
a1286344
16.8%
u602323
 
7.9%
l602323
 
7.9%
S372400
 
4.9%
i372400
 
4.9%
m372400
 
4.9%
I51984
 
0.7%
g51984
 
0.7%
Other values (3)155952
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7645444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1940651
25.4%
N1836683
24.0%
a1286344
16.8%
u602323
 
7.9%
l602323
 
7.9%
S372400
 
4.9%
i372400
 
4.9%
m372400
 
4.9%
I51984
 
0.7%
g51984
 
0.7%
Other values (3)155952
 
2.0%

desc_resp
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Sim
1265035 
Nao
579000 
Nulo
387692 
Ignorado
 
29340

Length

Max length8
Median length3
Mean length3.236345053
Min length3

Characters and Unicode

Total characters7317593
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowNao

Common Values

ValueCountFrequency (%)
Sim1265035
55.9%
Nao579000
25.6%
Nulo387692
 
17.1%
Ignorado29340
 
1.3%

Length

2021-10-10T23:42:31.379244image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:31.436092image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
sim1265035
55.9%
nao579000
25.6%
nulo387692
 
17.1%
ignorado29340
 
1.3%

Most occurring characters

ValueCountFrequency (%)
S1265035
17.3%
i1265035
17.3%
m1265035
17.3%
o1025372
14.0%
N966692
13.2%
a608340
8.3%
u387692
 
5.3%
l387692
 
5.3%
I29340
 
0.4%
g29340
 
0.4%
Other values (3)88020
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5056526
69.1%
Uppercase Letter2261067
30.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1265035
25.0%
m1265035
25.0%
o1025372
20.3%
a608340
12.0%
u387692
 
7.7%
l387692
 
7.7%
g29340
 
0.6%
n29340
 
0.6%
r29340
 
0.6%
d29340
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S1265035
55.9%
N966692
42.8%
I29340
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
Latin7317593
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1265035
17.3%
i1265035
17.3%
m1265035
17.3%
o1025372
14.0%
N966692
13.2%
a608340
8.3%
u387692
 
5.3%
l387692
 
5.3%
I29340
 
0.4%
g29340
 
0.4%
Other values (3)88020
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII7317593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1265035
17.3%
i1265035
17.3%
m1265035
17.3%
o1025372
14.0%
N966692
13.2%
a608340
8.3%
u387692
 
5.3%
l387692
 
5.3%
I29340
 
0.4%
g29340
 
0.4%
Other values (3)88020
 
1.2%

saturacao
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Sim
1371295 
Nao
521136 
Nulo
336189 
Ignorado
 
32447

Length

Max length8
Median length3
Mean length3.220437519
Min length3

Characters and Unicode

Total characters7281625
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowNao

Common Values

ValueCountFrequency (%)
Sim1371295
60.6%
Nao521136
 
23.0%
Nulo336189
 
14.9%
Ignorado32447
 
1.4%

Length

2021-10-10T23:42:31.593123image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:31.649476image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
sim1371295
60.6%
nao521136
 
23.0%
nulo336189
 
14.9%
ignorado32447
 
1.4%

Most occurring characters

ValueCountFrequency (%)
S1371295
18.8%
i1371295
18.8%
m1371295
18.8%
o922219
12.7%
N857325
11.8%
a553583
7.6%
u336189
 
4.6%
l336189
 
4.6%
I32447
 
0.4%
g32447
 
0.4%
Other values (3)97341
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5020558
68.9%
Uppercase Letter2261067
31.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1371295
27.3%
m1371295
27.3%
o922219
18.4%
a553583
11.0%
u336189
 
6.7%
l336189
 
6.7%
g32447
 
0.6%
n32447
 
0.6%
r32447
 
0.6%
d32447
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
S1371295
60.6%
N857325
37.9%
I32447
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
Latin7281625
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S1371295
18.8%
i1371295
18.8%
m1371295
18.8%
o922219
12.7%
N857325
11.8%
a553583
7.6%
u336189
 
4.6%
l336189
 
4.6%
I32447
 
0.4%
g32447
 
0.4%
Other values (3)97341
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII7281625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S1371295
18.8%
i1371295
18.8%
m1371295
18.8%
o922219
12.7%
N857325
11.8%
a553583
7.6%
u336189
 
4.6%
l336189
 
4.6%
I32447
 
0.4%
g32447
 
0.4%
Other values (3)97341
 
1.3%

dor_abd
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1127981 
Nulo
972931 
Sim
 
111422
Ignorado
 
48733

Length

Max length8
Median length3
Mean length3.538062782
Min length3

Characters and Unicode

Total characters7999797
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNulo
5th rowNulo

Common Values

ValueCountFrequency (%)
Nao1127981
49.9%
Nulo972931
43.0%
Sim111422
 
4.9%
Ignorado48733
 
2.2%

Length

2021-10-10T23:42:31.803066image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:31.858443image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1127981
49.9%
nulo972931
43.0%
sim111422
 
4.9%
ignorado48733
 
2.2%

Most occurring characters

ValueCountFrequency (%)
o2198378
27.5%
N2100912
26.3%
a1176714
14.7%
u972931
12.2%
l972931
12.2%
S111422
 
1.4%
i111422
 
1.4%
m111422
 
1.4%
I48733
 
0.6%
g48733
 
0.6%
Other values (3)146199
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5738730
71.7%
Uppercase Letter2261067
 
28.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2198378
38.3%
a1176714
20.5%
u972931
17.0%
l972931
17.0%
i111422
 
1.9%
m111422
 
1.9%
g48733
 
0.8%
n48733
 
0.8%
r48733
 
0.8%
d48733
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N2100912
92.9%
S111422
 
4.9%
I48733
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Latin7999797
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2198378
27.5%
N2100912
26.3%
a1176714
14.7%
u972931
12.2%
l972931
12.2%
S111422
 
1.4%
i111422
 
1.4%
m111422
 
1.4%
I48733
 
0.6%
g48733
 
0.6%
Other values (3)146199
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII7999797
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2198378
27.5%
N2100912
26.3%
a1176714
14.7%
u972931
12.2%
l972931
12.2%
S111422
 
1.4%
i111422
 
1.4%
m111422
 
1.4%
I48733
 
0.6%
g48733
 
0.6%
Other values (3)146199
 
1.8%

fadiga
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
907438 
Nao
874434 
Sim
433977 
Ignorado
 
45218

Length

Max length8
Median length3
Mean length3.501324375
Min length3

Characters and Unicode

Total characters7916729
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNulo
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo907438
40.1%
Nao874434
38.7%
Sim433977
19.2%
Ignorado45218
 
2.0%

Length

2021-10-10T23:42:32.003057image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:32.057910image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo907438
40.1%
nao874434
38.7%
sim433977
19.2%
ignorado45218
 
2.0%

Most occurring characters

ValueCountFrequency (%)
o1872308
23.7%
N1781872
22.5%
a919652
11.6%
u907438
11.5%
l907438
11.5%
S433977
 
5.5%
i433977
 
5.5%
m433977
 
5.5%
I45218
 
0.6%
g45218
 
0.6%
Other values (3)135654
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5655662
71.4%
Uppercase Letter2261067
 
28.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1872308
33.1%
a919652
16.3%
u907438
16.0%
l907438
16.0%
i433977
 
7.7%
m433977
 
7.7%
g45218
 
0.8%
n45218
 
0.8%
r45218
 
0.8%
d45218
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N1781872
78.8%
S433977
 
19.2%
I45218
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
Latin7916729
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1872308
23.7%
N1781872
22.5%
a919652
11.6%
u907438
11.5%
l907438
11.5%
S433977
 
5.5%
i433977
 
5.5%
m433977
 
5.5%
I45218
 
0.6%
g45218
 
0.6%
Other values (3)135654
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII7916729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1872308
23.7%
N1781872
22.5%
a919652
11.6%
u907438
11.5%
l907438
11.5%
S433977
 
5.5%
i433977
 
5.5%
m433977
 
5.5%
I45218
 
0.6%
g45218
 
0.6%
Other values (3)135654
 
1.7%

perd_olft
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1088750 
Nulo
956370 
Sim
159194 
Ignorado
 
56753

Length

Max length8
Median length3
Mean length3.548473354
Min length3

Characters and Unicode

Total characters8023336
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNulo
5th rowNulo

Common Values

ValueCountFrequency (%)
Nao1088750
48.2%
Nulo956370
42.3%
Sim159194
 
7.0%
Ignorado56753
 
2.5%

Length

2021-10-10T23:42:32.206521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:32.262391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1088750
48.2%
nulo956370
42.3%
sim159194
 
7.0%
ignorado56753
 
2.5%

Most occurring characters

ValueCountFrequency (%)
o2158626
26.9%
N2045120
25.5%
a1145503
14.3%
u956370
11.9%
l956370
11.9%
S159194
 
2.0%
i159194
 
2.0%
m159194
 
2.0%
I56753
 
0.7%
g56753
 
0.7%
Other values (3)170259
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5762269
71.8%
Uppercase Letter2261067
 
28.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2158626
37.5%
a1145503
19.9%
u956370
16.6%
l956370
16.6%
i159194
 
2.8%
m159194
 
2.8%
g56753
 
1.0%
n56753
 
1.0%
r56753
 
1.0%
d56753
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N2045120
90.4%
S159194
 
7.0%
I56753
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Latin8023336
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2158626
26.9%
N2045120
25.5%
a1145503
14.3%
u956370
11.9%
l956370
11.9%
S159194
 
2.0%
i159194
 
2.0%
m159194
 
2.0%
I56753
 
0.7%
g56753
 
0.7%
Other values (3)170259
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII8023336
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2158626
26.9%
N2045120
25.5%
a1145503
14.3%
u956370
11.9%
l956370
11.9%
S159194
 
2.0%
i159194
 
2.0%
m159194
 
2.0%
I56753
 
0.7%
g56753
 
0.7%
Other values (3)170259
 
2.1%

perd_pala
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1083987 
Nulo
957844 
Sim
161780 
Ignorado
 
57456

Length

Max length8
Median length3
Mean length3.550679834
Min length3

Characters and Unicode

Total characters8028325
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNulo
5th rowNulo

Common Values

ValueCountFrequency (%)
Nao1083987
47.9%
Nulo957844
42.4%
Sim161780
 
7.2%
Ignorado57456
 
2.5%

Length

2021-10-10T23:42:32.413909image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:32.468766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1083987
47.9%
nulo957844
42.4%
sim161780
 
7.2%
ignorado57456
 
2.5%

Most occurring characters

ValueCountFrequency (%)
o2156743
26.9%
N2041831
25.4%
a1141443
14.2%
u957844
11.9%
l957844
11.9%
S161780
 
2.0%
i161780
 
2.0%
m161780
 
2.0%
I57456
 
0.7%
g57456
 
0.7%
Other values (3)172368
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5767258
71.8%
Uppercase Letter2261067
 
28.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2156743
37.4%
a1141443
19.8%
u957844
16.6%
l957844
16.6%
i161780
 
2.8%
m161780
 
2.8%
g57456
 
1.0%
n57456
 
1.0%
r57456
 
1.0%
d57456
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
N2041831
90.3%
S161780
 
7.2%
I57456
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
Latin8028325
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2156743
26.9%
N2041831
25.4%
a1141443
14.2%
u957844
11.9%
l957844
11.9%
S161780
 
2.0%
i161780
 
2.0%
m161780
 
2.0%
I57456
 
0.7%
g57456
 
0.7%
Other values (3)172368
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII8028325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2156743
26.9%
N2041831
25.4%
a1141443
14.2%
u957844
11.9%
l957844
11.9%
S161780
 
2.0%
i161780
 
2.0%
m161780
 
2.0%
I57456
 
0.7%
g57456
 
0.7%
Other values (3)172368
 
2.1%

hematologi
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1395450 
Nao
826212 
Ignorado
 
22829
Sim
 
16576

Length

Max length8
Median length4
Mean length3.667647177
Min length3

Characters and Unicode

Total characters8292796
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1395450
61.7%
Nao826212
36.5%
Ignorado22829
 
1.0%
Sim16576
 
0.7%

Length

2021-10-10T23:42:32.626305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:32.684153image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1395450
61.7%
nao826212
36.5%
ignorado22829
 
1.0%
sim16576
 
0.7%

Most occurring characters

ValueCountFrequency (%)
o2267320
27.3%
N2221662
26.8%
u1395450
16.8%
l1395450
16.8%
a849041
 
10.2%
I22829
 
0.3%
g22829
 
0.3%
n22829
 
0.3%
r22829
 
0.3%
d22829
 
0.3%
Other values (3)49728
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6031729
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2267320
37.6%
u1395450
23.1%
l1395450
23.1%
a849041
 
14.1%
g22829
 
0.4%
n22829
 
0.4%
r22829
 
0.4%
d22829
 
0.4%
i16576
 
0.3%
m16576
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N2221662
98.3%
I22829
 
1.0%
S16576
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin8292796
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2267320
27.3%
N2221662
26.8%
u1395450
16.8%
l1395450
16.8%
a849041
 
10.2%
I22829
 
0.3%
g22829
 
0.3%
n22829
 
0.3%
r22829
 
0.3%
d22829
 
0.3%
Other values (3)49728
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII8292796
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2267320
27.3%
N2221662
26.8%
u1395450
16.8%
l1395450
16.8%
a849041
 
10.2%
I22829
 
0.3%
g22829
 
0.3%
n22829
 
0.3%
r22829
 
0.3%
d22829
 
0.3%
Other values (3)49728
 
0.6%

cardiopati
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1153453 
Sim
683945 
Nao
411338 
Ignorado
 
12331

Length

Max length8
Median length4
Mean length3.537404685
Min length3

Characters and Unicode

Total characters7998309
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowSim
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1153453
51.0%
Sim683945
30.2%
Nao411338
 
18.2%
Ignorado12331
 
0.5%

Length

2021-10-10T23:42:32.833773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:32.890620image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1153453
51.0%
sim683945
30.2%
nao411338
 
18.2%
ignorado12331
 
0.5%

Most occurring characters

ValueCountFrequency (%)
o1589453
19.9%
N1564791
19.6%
u1153453
14.4%
l1153453
14.4%
S683945
8.6%
i683945
8.6%
m683945
8.6%
a423669
 
5.3%
I12331
 
0.2%
g12331
 
0.2%
Other values (3)36993
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5737242
71.7%
Uppercase Letter2261067
 
28.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1589453
27.7%
u1153453
20.1%
l1153453
20.1%
i683945
11.9%
m683945
11.9%
a423669
 
7.4%
g12331
 
0.2%
n12331
 
0.2%
r12331
 
0.2%
d12331
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N1564791
69.2%
S683945
30.2%
I12331
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Latin7998309
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1589453
19.9%
N1564791
19.6%
u1153453
14.4%
l1153453
14.4%
S683945
8.6%
i683945
8.6%
m683945
8.6%
a423669
 
5.3%
I12331
 
0.2%
g12331
 
0.2%
Other values (3)36993
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII7998309
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1589453
19.9%
N1564791
19.6%
u1153453
14.4%
l1153453
14.4%
S683945
8.6%
i683945
8.6%
m683945
8.6%
a423669
 
5.3%
I12331
 
0.2%
g12331
 
0.2%
Other values (3)36993
 
0.5%

asma
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1380532 
Nao
785686 
Sim
 
73767
Ignorado
 
21082

Length

Max length8
Median length4
Mean length3.657186187
Min length3

Characters and Unicode

Total characters8269143
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1380532
61.1%
Nao785686
34.7%
Sim73767
 
3.3%
Ignorado21082
 
0.9%

Length

2021-10-10T23:42:33.048080image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:33.102936image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1380532
61.1%
nao785686
34.7%
sim73767
 
3.3%
ignorado21082
 
0.9%

Most occurring characters

ValueCountFrequency (%)
o2208382
26.7%
N2166218
26.2%
u1380532
16.7%
l1380532
16.7%
a806768
 
9.8%
S73767
 
0.9%
i73767
 
0.9%
m73767
 
0.9%
I21082
 
0.3%
g21082
 
0.3%
Other values (3)63246
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6008076
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2208382
36.8%
u1380532
23.0%
l1380532
23.0%
a806768
 
13.4%
i73767
 
1.2%
m73767
 
1.2%
g21082
 
0.4%
n21082
 
0.4%
r21082
 
0.4%
d21082
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N2166218
95.8%
S73767
 
3.3%
I21082
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin8269143
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2208382
26.7%
N2166218
26.2%
u1380532
16.7%
l1380532
16.7%
a806768
 
9.8%
S73767
 
0.9%
i73767
 
0.9%
m73767
 
0.9%
I21082
 
0.3%
g21082
 
0.3%
Other values (3)63246
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8269143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2208382
26.7%
N2166218
26.2%
u1380532
16.7%
l1380532
16.7%
a806768
 
9.8%
S73767
 
0.9%
i73767
 
0.9%
m73767
 
0.9%
I21082
 
0.3%
g21082
 
0.3%
Other values (3)63246
 
0.8%

diabetes
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1225805 
Nao
543860 
Sim
476567 
Ignorado
 
14835

Length

Max length8
Median length4
Mean length3.574940946
Min length3

Characters and Unicode

Total characters8083181
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowSim
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1225805
54.2%
Nao543860
24.1%
Sim476567
 
21.1%
Ignorado14835
 
0.7%

Length

2021-10-10T23:42:33.257074image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:33.314396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1225805
54.2%
nao543860
24.1%
sim476567
 
21.1%
ignorado14835
 
0.7%

Most occurring characters

ValueCountFrequency (%)
o1799335
22.3%
N1769665
21.9%
u1225805
15.2%
l1225805
15.2%
a558695
 
6.9%
S476567
 
5.9%
i476567
 
5.9%
m476567
 
5.9%
I14835
 
0.2%
g14835
 
0.2%
Other values (3)44505
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5822114
72.0%
Uppercase Letter2261067
 
28.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1799335
30.9%
u1225805
21.1%
l1225805
21.1%
a558695
 
9.6%
i476567
 
8.2%
m476567
 
8.2%
g14835
 
0.3%
n14835
 
0.3%
r14835
 
0.3%
d14835
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N1769665
78.3%
S476567
 
21.1%
I14835
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin8083181
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1799335
22.3%
N1769665
21.9%
u1225805
15.2%
l1225805
15.2%
a558695
 
6.9%
S476567
 
5.9%
i476567
 
5.9%
m476567
 
5.9%
I14835
 
0.2%
g14835
 
0.2%
Other values (3)44505
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII8083181
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1799335
22.3%
N1769665
21.9%
u1225805
15.2%
l1225805
15.2%
a558695
 
6.9%
S476567
 
5.9%
i476567
 
5.9%
m476567
 
5.9%
I14835
 
0.2%
g14835
 
0.2%
Other values (3)44505
 
0.6%

pneumopati
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1374306 
Nao
776280 
Sim
 
88689
Ignorado
 
21792

Length

Max length8
Median length4
Mean length3.656002675
Min length3

Characters and Unicode

Total characters8266467
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1374306
60.8%
Nao776280
34.3%
Sim88689
 
3.9%
Ignorado21792
 
1.0%

Length

2021-10-10T23:42:33.471871image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:33.526730image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1374306
60.8%
nao776280
34.3%
sim88689
 
3.9%
ignorado21792
 
1.0%

Most occurring characters

ValueCountFrequency (%)
o2194170
26.5%
N2150586
26.0%
u1374306
16.6%
l1374306
16.6%
a798072
 
9.7%
S88689
 
1.1%
i88689
 
1.1%
m88689
 
1.1%
I21792
 
0.3%
g21792
 
0.3%
Other values (3)65376
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6005400
72.6%
Uppercase Letter2261067
 
27.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2194170
36.5%
u1374306
22.9%
l1374306
22.9%
a798072
 
13.3%
i88689
 
1.5%
m88689
 
1.5%
g21792
 
0.4%
n21792
 
0.4%
r21792
 
0.4%
d21792
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N2150586
95.1%
S88689
 
3.9%
I21792
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8266467
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2194170
26.5%
N2150586
26.0%
u1374306
16.6%
l1374306
16.6%
a798072
 
9.7%
S88689
 
1.1%
i88689
 
1.1%
m88689
 
1.1%
I21792
 
0.3%
g21792
 
0.3%
Other values (3)65376
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8266467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2194170
26.5%
N2150586
26.0%
u1374306
16.6%
l1374306
16.6%
a798072
 
9.7%
S88689
 
1.1%
i88689
 
1.1%
m88689
 
1.1%
I21792
 
0.3%
g21792
 
0.3%
Other values (3)65376
 
0.8%

renal
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1380144 
Nao
782217 
Sim
 
77450
Ignorado
 
21256

Length

Max length8
Median length4
Mean length3.657399361
Min length3

Characters and Unicode

Total characters8269625
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1380144
61.0%
Nao782217
34.6%
Sim77450
 
3.4%
Ignorado21256
 
0.9%

Length

2021-10-10T23:42:33.684309image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:33.740540image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1380144
61.0%
nao782217
34.6%
sim77450
 
3.4%
ignorado21256
 
0.9%

Most occurring characters

ValueCountFrequency (%)
o2204873
26.7%
N2162361
26.1%
u1380144
16.7%
l1380144
16.7%
a803473
 
9.7%
S77450
 
0.9%
i77450
 
0.9%
m77450
 
0.9%
I21256
 
0.3%
g21256
 
0.3%
Other values (3)63768
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6008558
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2204873
36.7%
u1380144
23.0%
l1380144
23.0%
a803473
 
13.4%
i77450
 
1.3%
m77450
 
1.3%
g21256
 
0.4%
n21256
 
0.4%
r21256
 
0.4%
d21256
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N2162361
95.6%
S77450
 
3.4%
I21256
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin8269625
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2204873
26.7%
N2162361
26.1%
u1380144
16.7%
l1380144
16.7%
a803473
 
9.7%
S77450
 
0.9%
i77450
 
0.9%
m77450
 
0.9%
I21256
 
0.3%
g21256
 
0.3%
Other values (3)63768
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8269625
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2204873
26.7%
N2162361
26.1%
u1380144
16.7%
l1380144
16.7%
a803473
 
9.7%
S77450
 
0.9%
i77450
 
0.9%
m77450
 
0.9%
I21256
 
0.3%
g21256
 
0.3%
Other values (3)63768
 
0.8%

imunodepre
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1387210 
Nao
793624 
Sim
 
57930
Ignorado
 
22303

Length

Max length8
Median length4
Mean length3.662839712
Min length3

Characters and Unicode

Total characters8281926
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1387210
61.4%
Nao793624
35.1%
Sim57930
 
2.6%
Ignorado22303
 
1.0%

Length

2021-10-10T23:42:34.050947image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:34.106798image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1387210
61.4%
nao793624
35.1%
sim57930
 
2.6%
ignorado22303
 
1.0%

Most occurring characters

ValueCountFrequency (%)
o2225440
26.9%
N2180834
26.3%
u1387210
16.7%
l1387210
16.7%
a815927
 
9.9%
S57930
 
0.7%
i57930
 
0.7%
m57930
 
0.7%
I22303
 
0.3%
g22303
 
0.3%
Other values (3)66909
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6020859
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2225440
37.0%
u1387210
23.0%
l1387210
23.0%
a815927
 
13.6%
i57930
 
1.0%
m57930
 
1.0%
g22303
 
0.4%
n22303
 
0.4%
r22303
 
0.4%
d22303
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N2180834
96.5%
S57930
 
2.6%
I22303
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8281926
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2225440
26.9%
N2180834
26.3%
u1387210
16.7%
l1387210
16.7%
a815927
 
9.9%
S57930
 
0.7%
i57930
 
0.7%
m57930
 
0.7%
I22303
 
0.3%
g22303
 
0.3%
Other values (3)66909
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8281926
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2225440
26.9%
N2180834
26.3%
u1387210
16.7%
l1387210
16.7%
a815927
 
9.9%
S57930
 
0.7%
i57930
 
0.7%
m57930
 
0.7%
I22303
 
0.3%
g22303
 
0.3%
Other values (3)66909
 
0.8%

hepatica
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1397741 
Nao
821684 
Ignorado
 
22692
Sim
 
18950

Length

Max length8
Median length4
Mean length3.668357461
Min length3

Characters and Unicode

Total characters8294402
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1397741
61.8%
Nao821684
36.3%
Ignorado22692
 
1.0%
Sim18950
 
0.8%

Length

2021-10-10T23:42:34.265705image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:34.321556image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1397741
61.8%
nao821684
36.3%
ignorado22692
 
1.0%
sim18950
 
0.8%

Most occurring characters

ValueCountFrequency (%)
o2264809
27.3%
N2219425
26.8%
u1397741
16.9%
l1397741
16.9%
a844376
 
10.2%
I22692
 
0.3%
g22692
 
0.3%
n22692
 
0.3%
r22692
 
0.3%
d22692
 
0.3%
Other values (3)56850
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6033335
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2264809
37.5%
u1397741
23.2%
l1397741
23.2%
a844376
 
14.0%
g22692
 
0.4%
n22692
 
0.4%
r22692
 
0.4%
d22692
 
0.4%
i18950
 
0.3%
m18950
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N2219425
98.2%
I22692
 
1.0%
S18950
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin8294402
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2264809
27.3%
N2219425
26.8%
u1397741
16.9%
l1397741
16.9%
a844376
 
10.2%
I22692
 
0.3%
g22692
 
0.3%
n22692
 
0.3%
r22692
 
0.3%
d22692
 
0.3%
Other values (3)56850
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII8294402
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2264809
27.3%
N2219425
26.8%
u1397741
16.9%
l1397741
16.9%
a844376
 
10.2%
I22692
 
0.3%
g22692
 
0.3%
n22692
 
0.3%
r22692
 
0.3%
d22692
 
0.3%
Other values (3)56850
 
0.7%

neurologic
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1375110 
Nao
775830 
Sim
 
88703
Ignorado
 
21424

Length

Max length8
Median length4
Mean length3.655544484
Min length3

Characters and Unicode

Total characters8265431
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1375110
60.8%
Nao775830
34.3%
Sim88703
 
3.9%
Ignorado21424
 
0.9%

Length

2021-10-10T23:42:34.482899image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:34.542741image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1375110
60.8%
nao775830
34.3%
sim88703
 
3.9%
ignorado21424
 
0.9%

Most occurring characters

ValueCountFrequency (%)
o2193788
26.5%
N2150940
26.0%
u1375110
16.6%
l1375110
16.6%
a797254
 
9.6%
S88703
 
1.1%
i88703
 
1.1%
m88703
 
1.1%
I21424
 
0.3%
g21424
 
0.3%
Other values (3)64272
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6004364
72.6%
Uppercase Letter2261067
 
27.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2193788
36.5%
u1375110
22.9%
l1375110
22.9%
a797254
 
13.3%
i88703
 
1.5%
m88703
 
1.5%
g21424
 
0.4%
n21424
 
0.4%
r21424
 
0.4%
d21424
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
N2150940
95.1%
S88703
 
3.9%
I21424
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin8265431
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2193788
26.5%
N2150940
26.0%
u1375110
16.6%
l1375110
16.6%
a797254
 
9.6%
S88703
 
1.1%
i88703
 
1.1%
m88703
 
1.1%
I21424
 
0.3%
g21424
 
0.3%
Other values (3)64272
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII8265431
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2193788
26.5%
N2150940
26.0%
u1375110
16.6%
l1375110
16.6%
a797254
 
9.6%
S88703
 
1.1%
i88703
 
1.1%
m88703
 
1.1%
I21424
 
0.3%
g21424
 
0.3%
Other values (3)64272
 
0.8%

obesidade
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1354429 
Nao
719622 
Sim
158762 
Ignorado
 
28254

Length

Max length8
Median length4
Mean length3.661501406
Min length3

Characters and Unicode

Total characters8278900
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1354429
59.9%
Nao719622
31.8%
Sim158762
 
7.0%
Ignorado28254
 
1.2%

Length

2021-10-10T23:42:34.711290image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:34.768137image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1354429
59.9%
nao719622
31.8%
sim158762
 
7.0%
ignorado28254
 
1.2%

Most occurring characters

ValueCountFrequency (%)
o2130559
25.7%
N2074051
25.1%
u1354429
16.4%
l1354429
16.4%
a747876
 
9.0%
S158762
 
1.9%
i158762
 
1.9%
m158762
 
1.9%
I28254
 
0.3%
g28254
 
0.3%
Other values (3)84762
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6017833
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2130559
35.4%
u1354429
22.5%
l1354429
22.5%
a747876
 
12.4%
i158762
 
2.6%
m158762
 
2.6%
g28254
 
0.5%
n28254
 
0.5%
r28254
 
0.5%
d28254
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N2074051
91.7%
S158762
 
7.0%
I28254
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
Latin8278900
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2130559
25.7%
N2074051
25.1%
u1354429
16.4%
l1354429
16.4%
a747876
 
9.0%
S158762
 
1.9%
i158762
 
1.9%
m158762
 
1.9%
I28254
 
0.3%
g28254
 
0.3%
Other values (3)84762
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII8278900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2130559
25.7%
N2074051
25.1%
u1354429
16.4%
l1354429
16.4%
a747876
 
9.0%
S158762
 
1.9%
i158762
 
1.9%
m158762
 
1.9%
I28254
 
0.3%
g28254
 
0.3%
Other values (3)84762
 
1.0%

puerpera
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1398322 
Nao
834652 
Ignorado
 
20715
Sim
 
7378

Length

Max length8
Median length4
Mean length3.66424259
Min length3

Characters and Unicode

Total characters8285098
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1398322
61.8%
Nao834652
36.9%
Ignorado20715
 
0.9%
Sim7378
 
0.3%

Length

2021-10-10T23:42:34.928814image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:34.984666image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1398322
61.8%
nao834652
36.9%
ignorado20715
 
0.9%
sim7378
 
0.3%

Most occurring characters

ValueCountFrequency (%)
o2274404
27.5%
N2232974
27.0%
u1398322
16.9%
l1398322
16.9%
a855367
 
10.3%
I20715
 
0.3%
g20715
 
0.3%
n20715
 
0.3%
r20715
 
0.3%
d20715
 
0.3%
Other values (3)22134
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6024031
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2274404
37.8%
u1398322
23.2%
l1398322
23.2%
a855367
 
14.2%
g20715
 
0.3%
n20715
 
0.3%
r20715
 
0.3%
d20715
 
0.3%
i7378
 
0.1%
m7378
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N2232974
98.8%
I20715
 
0.9%
S7378
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin8285098
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2274404
27.5%
N2232974
27.0%
u1398322
16.9%
l1398322
16.9%
a855367
 
10.3%
I20715
 
0.3%
g20715
 
0.3%
n20715
 
0.3%
r20715
 
0.3%
d20715
 
0.3%
Other values (3)22134
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII8285098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2274404
27.5%
N2232974
27.0%
u1398322
16.9%
l1398322
16.9%
a855367
 
10.3%
I20715
 
0.3%
g20715
 
0.3%
n20715
 
0.3%
r20715
 
0.3%
d20715
 
0.3%
Other values (3)22134
 
0.3%

sind_down
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nulo
1398424 
Nao
835323 
Ignorado
 
20656
Sim
 
6664

Length

Max length8
Median length4
Mean length3.664157232
Min length3

Characters and Unicode

Total characters8284905
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowNulo
4th rowNao
5th rowNulo

Common Values

ValueCountFrequency (%)
Nulo1398424
61.8%
Nao835323
36.9%
Ignorado20656
 
0.9%
Sim6664
 
0.3%

Length

2021-10-10T23:42:35.141446image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:35.196300image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nulo1398424
61.8%
nao835323
36.9%
ignorado20656
 
0.9%
sim6664
 
0.3%

Most occurring characters

ValueCountFrequency (%)
o2275059
27.5%
N2233747
27.0%
u1398424
16.9%
l1398424
16.9%
a855979
 
10.3%
I20656
 
0.2%
g20656
 
0.2%
n20656
 
0.2%
r20656
 
0.2%
d20656
 
0.2%
Other values (3)19992
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6023838
72.7%
Uppercase Letter2261067
 
27.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2275059
37.8%
u1398424
23.2%
l1398424
23.2%
a855979
 
14.2%
g20656
 
0.3%
n20656
 
0.3%
r20656
 
0.3%
d20656
 
0.3%
i6664
 
0.1%
m6664
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
N2233747
98.8%
I20656
 
0.9%
S6664
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
Latin8284905
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2275059
27.5%
N2233747
27.0%
u1398424
16.9%
l1398424
16.9%
a855979
 
10.3%
I20656
 
0.2%
g20656
 
0.2%
n20656
 
0.2%
r20656
 
0.2%
d20656
 
0.2%
Other values (3)19992
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII8284905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2275059
27.5%
N2233747
27.0%
u1398424
16.9%
l1398424
16.9%
a855979
 
10.3%
I20656
 
0.2%
g20656
 
0.2%
n20656
 
0.2%
r20656
 
0.2%
d20656
 
0.2%
Other values (3)19992
 
0.2%

SG_UF_NOT
Categorical

Distinct27
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
SP
696100 
MG
256989 
RJ
181019 
PR
159939 
RS
134928 
Other values (22)
832092 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4522134
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDF
2nd rowDF
3rd rowCE
4th rowSP
5th rowSP

Common Values

ValueCountFrequency (%)
SP696100
30.8%
MG256989
 
11.4%
RJ181019
 
8.0%
PR159939
 
7.1%
RS134928
 
6.0%
SC84879
 
3.8%
BA84579
 
3.7%
GO81469
 
3.6%
CE76231
 
3.4%
PE72368
 
3.2%
Other values (17)432566
19.1%

Length

2021-10-10T23:42:35.361537image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sp696100
30.8%
mg256989
 
11.4%
rj181019
 
8.0%
pr159939
 
7.1%
rs134928
 
6.0%
sc84879
 
3.8%
ba84579
 
3.7%
go81469
 
3.6%
ce76231
 
3.4%
pe72368
 
3.2%
Other values (17)432566
19.1%

Most occurring characters

ValueCountFrequency (%)
P1047557
23.2%
S984304
21.8%
R521291
11.5%
M406424
 
9.0%
G338458
 
7.5%
A251638
 
5.6%
J181019
 
4.0%
E177108
 
3.9%
C167418
 
3.7%
B118636
 
2.6%
Other values (7)328281
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter4522134
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P1047557
23.2%
S984304
21.8%
R521291
11.5%
M406424
 
9.0%
G338458
 
7.5%
A251638
 
5.6%
J181019
 
4.0%
E177108
 
3.9%
C167418
 
3.7%
B118636
 
2.6%
Other values (7)328281
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
Latin4522134
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P1047557
23.2%
S984304
21.8%
R521291
11.5%
M406424
 
9.0%
G338458
 
7.5%
A251638
 
5.6%
J181019
 
4.0%
E177108
 
3.9%
C167418
 
3.7%
B118636
 
2.6%
Other values (7)328281
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII4522134
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P1047557
23.2%
S984304
21.8%
R521291
11.5%
M406424
 
9.0%
G338458
 
7.5%
A251638
 
5.6%
J181019
 
4.0%
E177108
 
3.9%
C167418
 
3.7%
B118636
 
2.6%
Other values (7)328281
 
7.3%

idade
Real number (ℝ≥0)

Distinct180
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.64376361
Minimum0
Maximum121
Zeros4397
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size17.3 MiB
2021-10-10T23:42:35.455289image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q143
median58
Q372
95-th percentile87
Maximum121
Range121
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.75996816
Coefficient of variation (CV)0.3910585257
Kurtosis0.09767200706
Mean55.64376361
Median Absolute Deviation (MAD)14
Skewness-0.6158975372
Sum125814277.7
Variance473.4962144
MonotonicityNot monotonic
2021-10-10T23:42:35.574405image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5743712
 
1.9%
5843699
 
1.9%
5943538
 
1.9%
6642795
 
1.9%
5642688
 
1.9%
6242414
 
1.9%
6342347
 
1.9%
6442228
 
1.9%
6542124
 
1.9%
5542029
 
1.9%
Other values (170)1833493
81.1%
ValueCountFrequency (%)
04397
0.2%
0.003409
 
< 0.1%
0.005216
 
< 0.1%
0.008158
 
< 0.1%
0.011102
 
< 0.1%
0.014117
 
< 0.1%
0.016114
 
< 0.1%
0.019157
 
< 0.1%
0.022175
 
< 0.1%
0.025168
 
< 0.1%
ValueCountFrequency (%)
1211
 
< 0.1%
1204
 
< 0.1%
1191
 
< 0.1%
1181
 
< 0.1%
1174
 
< 0.1%
1161
 
< 0.1%
1158
< 0.1%
11415
< 0.1%
11312
< 0.1%
11210
< 0.1%

CS_SEXO
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
M
1236315 
F
1024752 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowM
3rd rowM
4th rowF
5th rowF

Common Values

ValueCountFrequency (%)
M1236315
54.7%
F1024752
45.3%

Length

2021-10-10T23:42:35.747459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:35.799327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
m1236315
54.7%
f1024752
45.3%

Most occurring characters

ValueCountFrequency (%)
M1236315
54.7%
F1024752
45.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter2261067
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
M1236315
54.7%
F1024752
45.3%

Most occurring scripts

ValueCountFrequency (%)
Latin2261067
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
M1236315
54.7%
F1024752
45.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
M1236315
54.7%
F1024752
45.3%

gravidez
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2239774 
1
 
21293

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

Length

2021-10-10T23:42:35.929315image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:35.981171image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

Most occurring characters

ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02239774
99.1%
121293
 
0.9%

raca
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Branca
948368 
Parda
769879 
Ignorado
372278 
Preta
102223 
Desconhecido
 
41719
Other values (2)
 
26600

Length

Max length12
Median length6
Mean length6.068096169
Min length5

Characters and Unicode

Total characters13720372
Distinct characters19
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowParda
2nd rowParda
3rd rowParda
4th rowBranca
5th rowBranca

Common Values

ValueCountFrequency (%)
Branca948368
41.9%
Parda769879
34.0%
Ignorado372278
 
16.5%
Preta102223
 
4.5%
Desconhecido41719
 
1.8%
Amarela21998
 
1.0%
Indigena4602
 
0.2%

Length

2021-10-10T23:42:36.125763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:36.195577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
branca948368
41.9%
parda769879
34.0%
ignorado372278
 
16.5%
preta102223
 
4.5%
desconhecido41719
 
1.8%
amarela21998
 
1.0%
indigena4602
 
0.2%

Most occurring characters

ValueCountFrequency (%)
a3959593
28.9%
r2214746
16.1%
n1371569
 
10.0%
d1188478
 
8.7%
c1031806
 
7.5%
B948368
 
6.9%
P872102
 
6.4%
o827994
 
6.0%
I376880
 
2.7%
g376880
 
2.7%
Other values (9)551956
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter11459305
83.5%
Uppercase Letter2261067
 
16.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a3959593
34.6%
r2214746
19.3%
n1371569
 
12.0%
d1188478
 
10.4%
c1031806
 
9.0%
o827994
 
7.2%
g376880
 
3.3%
e212261
 
1.9%
t102223
 
0.9%
i46321
 
0.4%
Other values (4)127434
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
B948368
41.9%
P872102
38.6%
I376880
 
16.7%
D41719
 
1.8%
A21998
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Latin13720372
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a3959593
28.9%
r2214746
16.1%
n1371569
 
10.0%
d1188478
 
8.7%
c1031806
 
7.5%
B948368
 
6.9%
P872102
 
6.4%
o827994
 
6.0%
I376880
 
2.7%
g376880
 
2.7%
Other values (9)551956
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII13720372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a3959593
28.9%
r2214746
16.1%
n1371569
 
10.0%
d1188478
 
8.7%
c1031806
 
7.5%
B948368
 
6.9%
P872102
 
6.4%
o827994
 
6.0%
I376880
 
2.7%
g376880
 
2.7%
Other values (9)551956
 
4.0%

vacina_gripe
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Ignorado
800528 
Nao
705854 
Nulo
514633 
Sim
240052 

Length

Max length8
Median length4
Mean length4.99785013
Min length3

Characters and Unicode

Total characters11300474
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowSim
3rd rowNulo
4th rowIgnorado
5th rowSim

Common Values

ValueCountFrequency (%)
Ignorado800528
35.4%
Nao705854
31.2%
Nulo514633
22.8%
Sim240052
 
10.6%

Length

2021-10-10T23:42:36.363128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:36.420974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
ignorado800528
35.4%
nao705854
31.2%
nulo514633
22.8%
sim240052
 
10.6%

Most occurring characters

ValueCountFrequency (%)
o2821543
25.0%
a1506382
13.3%
N1220487
10.8%
I800528
 
7.1%
g800528
 
7.1%
n800528
 
7.1%
r800528
 
7.1%
d800528
 
7.1%
u514633
 
4.6%
l514633
 
4.6%
Other values (3)720156
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter9039407
80.0%
Uppercase Letter2261067
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2821543
31.2%
a1506382
16.7%
g800528
 
8.9%
n800528
 
8.9%
r800528
 
8.9%
d800528
 
8.9%
u514633
 
5.7%
l514633
 
5.7%
i240052
 
2.7%
m240052
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
N1220487
54.0%
I800528
35.4%
S240052
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
Latin11300474
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2821543
25.0%
a1506382
13.3%
N1220487
10.8%
I800528
 
7.1%
g800528
 
7.1%
n800528
 
7.1%
r800528
 
7.1%
d800528
 
7.1%
u514633
 
4.6%
l514633
 
4.6%
Other values (3)720156
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII11300474
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2821543
25.0%
a1506382
13.3%
N1220487
10.8%
I800528
 
7.1%
g800528
 
7.1%
n800528
 
7.1%
r800528
 
7.1%
d800528
 
7.1%
u514633
 
4.6%
l514633
 
4.6%
Other values (3)720156
 
6.4%

mae_amamenta
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2235722 
1
 
25345

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%

Length

2021-10-10T23:42:36.556612image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:36.606478image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%

Most occurring characters

ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02235722
98.9%
125345
 
1.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2259419 
1
 
1648

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

Length

2021-10-10T23:42:36.733039image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:36.934003image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

Most occurring characters

ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02259419
99.9%
11648
 
0.1%

EVOLUCAO
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
1563843 
1
697224 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

Length

2021-10-10T23:42:37.057624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:37.108487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

Most occurring characters

ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
01563843
69.2%
1697224
30.8%

diagnostico
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
COVID
1641389 
Desconhecido
596406 
Outros
 
20189
Influenza
 
3083

Length

Max length12
Median length5
Mean length6.860786522
Min length5

Characters and Unicode

Total characters15512698
Distinct characters20
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOutros
2nd rowDesconhecido
3rd rowOutros
4th rowDesconhecido
5th rowDesconhecido

Common Values

ValueCountFrequency (%)
COVID1641389
72.6%
Desconhecido596406
 
26.4%
Outros20189
 
0.9%
Influenza3083
 
0.1%

Length

2021-10-10T23:42:37.261079image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:37.323110image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
covid1641389
72.6%
desconhecido596406
 
26.4%
outros20189
 
0.9%
influenza3083
 
0.1%

Most occurring characters

ValueCountFrequency (%)
D2237795
14.4%
O1661578
10.7%
I1644472
10.6%
C1641389
10.6%
V1641389
10.6%
o1213001
7.8%
e1195895
7.7%
c1192812
7.7%
s616595
 
4.0%
n602572
 
3.9%
Other values (10)1865200
12.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter8826623
56.9%
Lowercase Letter6686075
43.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1213001
18.1%
e1195895
17.9%
c1192812
17.8%
s616595
9.2%
n602572
9.0%
h596406
8.9%
i596406
8.9%
d596406
8.9%
u23272
 
0.3%
t20189
 
0.3%
Other values (5)32521
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
D2237795
25.4%
O1661578
18.8%
I1644472
18.6%
C1641389
18.6%
V1641389
18.6%

Most occurring scripts

ValueCountFrequency (%)
Latin15512698
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
D2237795
14.4%
O1661578
10.7%
I1644472
10.6%
C1641389
10.6%
V1641389
10.6%
o1213001
7.8%
e1195895
7.7%
c1192812
7.7%
s616595
 
4.0%
n602572
 
3.9%
Other values (10)1865200
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII15512698
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
D2237795
14.4%
O1661578
10.7%
I1644472
10.6%
C1641389
10.6%
V1641389
10.6%
o1213001
7.8%
e1195895
7.7%
c1192812
7.7%
s616595
 
4.0%
n602572
 
3.9%
Other values (10)1865200
12.0%

antiviral
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1409389 
Nulo
334471 
Ignorado
317549 
Sim
199658 

Length

Max length8
Median length3
Mean length3.850136683
Min length3

Characters and Unicode

Total characters8705417
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowNao
3rd rowSim
4th rowSim
5th rowNao

Common Values

ValueCountFrequency (%)
Nao1409389
62.3%
Nulo334471
 
14.8%
Ignorado317549
 
14.0%
Sim199658
 
8.8%

Length

2021-10-10T23:42:37.477716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:37.536677image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1409389
62.3%
nulo334471
 
14.8%
ignorado317549
 
14.0%
sim199658
 
8.8%

Most occurring characters

ValueCountFrequency (%)
o2378958
27.3%
N1743860
20.0%
a1726938
19.8%
u334471
 
3.8%
l334471
 
3.8%
I317549
 
3.6%
g317549
 
3.6%
n317549
 
3.6%
r317549
 
3.6%
d317549
 
3.6%
Other values (3)598974
 
6.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter6444350
74.0%
Uppercase Letter2261067
 
26.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2378958
36.9%
a1726938
26.8%
u334471
 
5.2%
l334471
 
5.2%
g317549
 
4.9%
n317549
 
4.9%
r317549
 
4.9%
d317549
 
4.9%
i199658
 
3.1%
m199658
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
N1743860
77.1%
I317549
 
14.0%
S199658
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Latin8705417
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2378958
27.3%
N1743860
20.0%
a1726938
19.8%
u334471
 
3.8%
l334471
 
3.8%
I317549
 
3.6%
g317549
 
3.6%
n317549
 
3.6%
r317549
 
3.6%
d317549
 
3.6%
Other values (3)598974
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII8705417
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2378958
27.3%
N1743860
20.0%
a1726938
19.8%
u334471
 
3.8%
l334471
 
3.8%
I317549
 
3.6%
g317549
 
3.6%
n317549
 
3.6%
r317549
 
3.6%
d317549
 
3.6%
Other values (3)598974
 
6.9%

suporte_vent
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao-invasivo
1082738 
Nao
461868 
Invasivo
376032 
Nulo
268184 
Ignorado
 
72245

Length

Max length12
Median length8
Mean length8.419658506
Min length3

Characters and Unicode

Total characters19037412
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao-invasivo
2nd rowNao-invasivo
3rd rowInvasivo
4th rowInvasivo
5th rowNao

Common Values

ValueCountFrequency (%)
Nao-invasivo1082738
47.9%
Nao461868
20.4%
Invasivo376032
 
16.6%
Nulo268184
 
11.9%
Ignorado72245
 
3.2%

Length

2021-10-10T23:42:37.686689image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:37.744684image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao-invasivo1082738
47.9%
nao461868
20.4%
invasivo376032
 
16.6%
nulo268184
 
11.9%
ignorado72245
 
3.2%

Most occurring characters

ValueCountFrequency (%)
o3416050
17.9%
a3075621
16.2%
v2917540
15.3%
i2541508
13.4%
N1812790
9.5%
n1531015
8.0%
s1458770
7.7%
-1082738
 
5.7%
I448277
 
2.4%
u268184
 
1.4%
Other values (4)484919
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15693607
82.4%
Uppercase Letter2261067
 
11.9%
Dash Punctuation1082738
 
5.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3416050
21.8%
a3075621
19.6%
v2917540
18.6%
i2541508
16.2%
n1531015
9.8%
s1458770
9.3%
u268184
 
1.7%
l268184
 
1.7%
g72245
 
0.5%
r72245
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
N1812790
80.2%
I448277
 
19.8%
Dash Punctuation
ValueCountFrequency (%)
-1082738
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17954674
94.3%
Common1082738
 
5.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3416050
19.0%
a3075621
17.1%
v2917540
16.2%
i2541508
14.2%
N1812790
10.1%
n1531015
8.5%
s1458770
8.1%
I448277
 
2.5%
u268184
 
1.5%
l268184
 
1.5%
Other values (3)216735
 
1.2%
Common
ValueCountFrequency (%)
-1082738
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19037412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3416050
17.9%
a3075621
16.2%
v2917540
15.3%
i2541508
13.4%
N1812790
9.5%
n1531015
8.0%
s1458770
7.7%
-1082738
 
5.7%
I448277
 
2.4%
u268184
 
1.4%
Other values (4)484919
 
2.5%

uti
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao
1259631 
Sim
700857 
Nulo
261177 
Ignorado
 
39402

Length

Max length8
Median length3
Mean length3.202641939
Min length3

Characters and Unicode

Total characters7241388
Distinct characters13
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao
2nd rowNao
3rd rowNao
4th rowSim
5th rowNulo

Common Values

ValueCountFrequency (%)
Nao1259631
55.7%
Sim700857
31.0%
Nulo261177
 
11.6%
Ignorado39402
 
1.7%

Length

2021-10-10T23:42:37.906437image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:37.963285image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao1259631
55.7%
sim700857
31.0%
nulo261177
 
11.6%
ignorado39402
 
1.7%

Most occurring characters

ValueCountFrequency (%)
o1599612
22.1%
N1520808
21.0%
a1299033
17.9%
S700857
9.7%
i700857
9.7%
m700857
9.7%
u261177
 
3.6%
l261177
 
3.6%
I39402
 
0.5%
g39402
 
0.5%
Other values (3)118206
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter4980321
68.8%
Uppercase Letter2261067
31.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o1599612
32.1%
a1299033
26.1%
i700857
14.1%
m700857
14.1%
u261177
 
5.2%
l261177
 
5.2%
g39402
 
0.8%
n39402
 
0.8%
r39402
 
0.8%
d39402
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
N1520808
67.3%
S700857
31.0%
I39402
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin7241388
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o1599612
22.1%
N1520808
21.0%
a1299033
17.9%
S700857
9.7%
i700857
9.7%
m700857
9.7%
u261177
 
3.6%
l261177
 
3.6%
I39402
 
0.5%
g39402
 
0.5%
Other values (3)118206
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII7241388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o1599612
22.1%
N1520808
21.0%
a1299033
17.9%
S700857
9.7%
i700857
9.7%
m700857
9.7%
u261177
 
3.6%
l261177
 
3.6%
I39402
 
0.5%
g39402
 
0.5%
Other values (3)118206
 
1.6%

positivo_vsr
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2252133 
1
 
8934

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

Length

2021-10-10T23:42:38.107333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:38.160192image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

Most occurring characters

ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02252133
99.6%
18934
 
0.4%

positivo_para1
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260856 
1
 
211

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

Length

2021-10-10T23:42:38.290347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:38.342208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260856
> 99.9%
1211
 
< 0.1%

positivo_para2
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260982 
1
 
85

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

Length

2021-10-10T23:42:38.470495image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:38.521359image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260982
> 99.9%
185
 
< 0.1%

positivo_para3
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260741 
1
 
326

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

Length

2021-10-10T23:42:38.647023image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:38.697363image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260741
> 99.9%
1326
 
< 0.1%

positivo_para4
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260905 
1
 
162

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

Length

2021-10-10T23:42:38.823593image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:38.874475image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260905
> 99.9%
1162
 
< 0.1%

positivo_adeno
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260258 
1
 
809

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

Length

2021-10-10T23:42:39.000951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.050817image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260258
> 99.9%
1809
 
< 0.1%

positivo_sars2
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
1
1257008 
0
1004059 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%

Length

2021-10-10T23:42:39.181469image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.237319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%

Most occurring characters

ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11257008
55.6%
01004059
44.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2258571 
1
 
2496

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

Length

2021-10-10T23:42:39.366972image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.418833image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

Most occurring characters

ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02258571
99.9%
12496
 
0.1%

positivo_metap
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260631 
1
 
436

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

Length

2021-10-10T23:42:39.547949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.598812image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260631
> 99.9%
1436
 
< 0.1%

positivo_boca
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2260637 
1
 
430

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

Length

2021-10-10T23:42:39.739437image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.792295image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02260637
> 99.9%
1430
 
< 0.1%

positivo_rino
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
0
2256175 
1
 
4892

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2261067
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

Length

2021-10-10T23:42:39.921570image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:39.973430image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

Most occurring characters

ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2261067
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Common2261067
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII2261067
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02256175
99.8%
14892
 
0.2%

vacina_covid19
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.3 MiB
Nao-disponivel
1028071 
Nulo
435209 
Nao
405788 
Ignorado
206526 
Sim
185473 

Length

Max length14
Median length8
Mean length8.650703849
Min length3

Characters and Unicode

Total characters19559821
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNao-disponivel
2nd rowNao-disponivel
3rd rowNao-disponivel
4th rowNao-disponivel
5th rowNao-disponivel

Common Values

ValueCountFrequency (%)
Nao-disponivel1028071
45.5%
Nulo435209
19.2%
Nao405788
 
17.9%
Ignorado206526
 
9.1%
Sim185473
 
8.2%

Length

2021-10-10T23:42:40.114054image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-10-10T23:42:40.171900image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
nao-disponivel1028071
45.5%
nulo435209
19.2%
nao405788
 
17.9%
ignorado206526
 
9.1%
sim185473
 
8.2%

Most occurring characters

ValueCountFrequency (%)
o3310191
16.9%
i2241615
11.5%
N1869068
9.6%
a1640385
8.4%
l1463280
7.5%
d1234597
 
6.3%
n1234597
 
6.3%
-1028071
 
5.3%
s1028071
 
5.3%
p1028071
 
5.3%
Other values (8)3481875
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16270683
83.2%
Uppercase Letter2261067
 
11.6%
Dash Punctuation1028071
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3310191
20.3%
i2241615
13.8%
a1640385
10.1%
l1463280
9.0%
d1234597
 
7.6%
n1234597
 
7.6%
s1028071
 
6.3%
p1028071
 
6.3%
v1028071
 
6.3%
e1028071
 
6.3%
Other values (4)1033734
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
N1869068
82.7%
I206526
 
9.1%
S185473
 
8.2%
Dash Punctuation
ValueCountFrequency (%)
-1028071
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin18531750
94.7%
Common1028071
 
5.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3310191
17.9%
i2241615
12.1%
N1869068
10.1%
a1640385
8.9%
l1463280
7.9%
d1234597
 
6.7%
n1234597
 
6.7%
s1028071
 
5.5%
p1028071
 
5.5%
v1028071
 
5.5%
Other values (7)2453804
13.2%
Common
ValueCountFrequency (%)
-1028071
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII19559821
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3310191
16.9%
i2241615
11.5%
N1869068
9.6%
a1640385
8.4%
l1463280
7.5%
d1234597
 
6.3%
n1234597
 
6.3%
-1028071
 
5.3%
s1028071
 
5.3%
p1028071
 
5.3%
Other values (8)3481875
17.8%

Interactions

2021-10-10T23:42:05.761260image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-10T23:42:06.483165image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-10T23:42:07.174316image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-10-10T23:42:07.842087image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-10-10T23:42:40.253690image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Missing values

2021-10-10T23:42:16.855783image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

DT_NOTIFICtempo_alta_obito_finalfebretossedispneiadiarreiavomitogargantadesc_respsaturacaodor_abdfadigaperd_olftperd_palahematologicardiopatiasmadiabetespneumopatirenalimunodeprehepaticaneurologicobesidadepuerperasind_downSG_UF_NOTidadeCS_SEXOgravidezracavacina_gripemae_amamentamae_vacinada_gripeEVOLUCAOdiagnosticoantiviralsuporte_ventutipositivo_vsrpositivo_para1positivo_para2positivo_para3positivo_para4positivo_adenopositivo_sars2positivo_influenzapositivo_metappositivo_bocapositivo_rinovacina_covid19
02020-10-01153.0SimSimSimNaoNaoNaoSimSimNuloNuloNuloNuloNuloNuloNuloNuloSimNuloSimNuloNuloNuloNuloNuloDF0.583M0PardaNao000OutrosNaoNao-invasivoNao00000010001Nao-disponivel
12020-07-01153.0SimSimIgnoradoNaoNaoNaoSimSimNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloDF1.000M0PardaSim000DesconhecidoNaoNao-invasivoNao00000000000Nao-disponivel
22020-01-27128.0SimSimSimSimSimNaoSimSimNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloCE0.750M0PardaNulo000OutrosSimInvasivoNao00000110000Nao-disponivel
32020-02-13171.0SimSimSimNaoNaoNaoSimSimNuloNuloNuloNuloNaoSimNaoSimNaoNaoNaoNaoNaoNaoNaoNaoSP57.000F0BrancaIgnorado001DesconhecidoSimInvasivoSim00000000000Nao-disponivel
42020-02-2621.0SimSimNaoNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloSP28.000F0BrancaSim000DesconhecidoNaoNaoNulo00000000000Nao-disponivel
52020-09-03153.0SimSimSimNaoNaoSimNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloPR29.000F1BrancaNao000InfluenzaSimNao-invasivoNao00000001000Nao-disponivel
62020-12-03159.0SimSimSimNaoNaoSimNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloMG32.000M0BrancaIgnorado000InfluenzaNaoNaoNulo00000001000Nao-disponivel
72020-12-0317.0SimSimSimSimSimSimSimSimNuloNuloNuloNuloNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoDF55.000F0PardaNao000DesconhecidoNaoNao-invasivoNao00000000000Nao-disponivel
82020-03-2028.0SimSimSimNaoNaoNaoSimNuloNuloNuloNuloNuloNaoSimNaoNaoNaoNaoNaoNaoSimNaoNaoNaoSP83.000M0BrancaIgnorado001DesconhecidoSimNao-invasivoNao00000000000Nao-disponivel
92020-03-22167.0SimSimNaoNaoNaoNaoSimSimNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloSP64.000M0DesconhecidoNao000DesconhecidoNaoNaoSim00000000000Nao-disponivel

Last rows

DT_NOTIFICtempo_alta_obito_finalfebretossedispneiadiarreiavomitogargantadesc_respsaturacaodor_abdfadigaperd_olftperd_palahematologicardiopatiasmadiabetespneumopatirenalimunodeprehepaticaneurologicobesidadepuerperasind_downSG_UF_NOTidadeCS_SEXOgravidezracavacina_gripemae_amamentamae_vacinada_gripeEVOLUCAOdiagnosticoantiviralsuporte_ventutipositivo_vsrpositivo_para1positivo_para2positivo_para3positivo_para4positivo_adenopositivo_sars2positivo_influenzapositivo_metappositivo_bocapositivo_rinovacina_covid19
22610572021-12-0938.0SimSimSimNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloPB8.0M0PardaNulo000DesconhecidoIgnoradoNao-invasivoNao00000000000Nao
22610582021-08-248.0NaoSimSimNaoNaoNaoSimSimNaoNaoNaoNaoNaoSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoPI58.0M0IgnoradoIgnorado000COVIDNaoNao-invasivoSim00000000000Ignorado
22610592021-09-13136.0NaoSimSimNaoNaoNaoNaoSimNaoSimNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloPR56.0M0BrancaNao000COVIDNaoNao-invasivoNao00000010000Nao
22610602021-09-2812.0SimSimSimNaoNaoNaoSimSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoSimNaoNaoNaoDF97.0F0IgnoradoIgnorado001COVIDNaoNao-invasivoNao00000010000Sim
22610612021-06-09190.0NaoNaoSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloMG73.0F0PardaIgnorado000COVIDNaoNao-invasivoNao00000010000Ignorado
22610622021-09-3082.0SimSimSimNaoNaoSimNaoNaoNaoNaoNaoNaoNaoSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoMA61.0F0PardaNao000DesconhecidoNaoNao-invasivoNao00000000000Nao
22610632021-09-248.0NaoNaoNaoNaoNaoNaoNaoSimSimNaoNaoNaoSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoMG71.0F0BrancaIgnorado000DesconhecidoIgnoradoNaoNao00000000000Ignorado
22610642021-09-253.0NaoSimNaoNaoNaoSimSimNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloRS41.0F0BrancaNulo000DesconhecidoNaoNaoNao00000000000Sim
22610652021-09-0572.0NaoSimSimNaoNaoNaoSimNaoNaoNaoNaoNaoNaoSimNaoSimNaoNaoNaoNaoNaoNaoIgnoradoNaoCE60.0M0PardaIgnorado000COVIDIgnoradoNao-invasivoNao00000010000Ignorado
22610662021-09-264.0SimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoSimNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoSP93.0F0BrancaSim000DesconhecidoNaoNao-invasivoNao00000000000Sim

Duplicate rows

Most frequently occurring

DT_NOTIFICtempo_alta_obito_finalfebretossedispneiadiarreiavomitogargantadesc_respsaturacaodor_abdfadigaperd_olftperd_palahematologicardiopatiasmadiabetespneumopatirenalimunodeprehepaticaneurologicobesidadepuerperasind_downSG_UF_NOTidadeCS_SEXOgravidezracavacina_gripemae_amamentamae_vacinada_gripeEVOLUCAOdiagnosticoantiviralsuporte_ventutipositivo_vsrpositivo_para1positivo_para2positivo_para3positivo_para4positivo_adenopositivo_sars2positivo_influenzapositivo_metappositivo_bocapositivo_rinovacina_covid19# duplicates
1442021-03-290.0NuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloRJ61.0F0BrancaNulo001COVIDNuloNuloNulo00000000000Nulo3
1822021-07-210.0NuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloSP56.0M0IgnoradoNulo001COVIDNuloNuloNulo00000000000Nulo3
1942021-08-211.0NaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloMS9.0M0BrancaNao000DesconhecidoNaoNaoNao00000000000Nao3
2052021-09-06-999.0NuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloAL78.0F0PardaNulo000COVIDNuloNuloNulo00000000000Nulo3
02020-01-050.0NuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloRJ71.0F0PardaNulo001COVIDNuloNuloNulo00000000000Nao-disponivel2
12020-01-06191.0SimNaoNaoNaoNaoNaoNaoNaoNuloNuloNuloNuloNaoSimNaoSimNaoNaoNaoNaoNaoNaoNaoNaoMT57.0F0PardaSim000COVIDSimNaoNulo00000010000Nao-disponivel2
22020-01-06192.0NaoNaoNaoNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloMT3.0F0PardaSim000COVIDNaoNaoNulo00000010000Nao-disponivel2
32020-01-08171.0NaoSimSimNaoNaoSimSimNaoNaoNaoNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloPR8.0M0BrancaNao000DesconhecidoNaoNaoNao00000000000Nao-disponivel2
42020-01-0917.0NaoNaoNaoNaoNaoNaoSimNaoNaoSimSimSimNaoSimNaoNaoNaoNaoNaoNaoSimNaoNaoNaoSP59.0F0BrancaSim000COVIDNaoNaoNao00000010000Nao-disponivel2
52020-01-09204.0NaoNaoSimNaoNaoNaoSimSimNaoSimNaoNaoNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloNuloGO79.0F0IgnoradoIgnorado001DesconhecidoNaoInvasivoNao00000000000Nao-disponivel2